def test_normalise_vector(self):
"""
Tests :func:`colour.algebra.geometry.normalise_vector` definition.
"""
np.testing.assert_almost_equal(
normalise_vector(np.array([0.20654008, 0.12197225, 0.05136952])),
np.array([0.84197033, 0.49722560, 0.20941026]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.14222010, 0.23042768, 0.10495772])),
np.array([0.48971705, 0.79344877, 0.36140872]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.07818780, 0.06157201, 0.28099326])),
np.array([0.26229003, 0.20655044, 0.94262445]),
decimal=7)
def test_normalise_vector(self):
"""
Tests :func:`colour.algebra.geometry.normalise_vector` definition.
"""
np.testing.assert_almost_equal(
normalise_vector(np.array([0.07049534, 0.10080000, 0.09558313])),
np.array([0.45254109, 0.64708025, 0.61359083]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.47097710, 0.34950000, 0.11301649])),
np.array([0.78853763, 0.58515351, 0.18921887]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.25506814, 0.19150000, 0.08849752])),
np.array([0.77058870, 0.57854241, 0.26736067]),
decimal=7)
def test_normalise_vector(self):
"""
Tests :func:`colour.algebra.geometry.normalise_vector` definition.
"""
np.testing.assert_almost_equal(
normalise_vector(np.array([0.07049534, 0.10080000, 0.09558313])),
np.array([0.45254109, 0.64708025, 0.61359083]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.47097710, 0.34950000, 0.11301649])),
np.array([0.78853763, 0.58515351, 0.18921887]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.25506814, 0.19150000, 0.08849752])),
np.array([0.77058870, 0.57854241, 0.26736067]),
decimal=7)
def test_normalise_vector(self):
"""
Tests :func:`colour.algebra.geometry.normalise_vector` definition.
"""
np.testing.assert_almost_equal(
normalise_vector(np.array([0.20654008, 0.12197225, 0.05136952])),
np.array([0.84197033, 0.49722560, 0.20941026]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.14222010, 0.23042768, 0.10495772])),
np.array([0.48971705, 0.79344877, 0.36140872]),
decimal=7)
np.testing.assert_almost_equal(
normalise_vector(np.array([0.07818780, 0.06157201, 0.28099326])),
np.array([0.26229003, 0.20655044, 0.94262445]),
decimal=7)
def CIE_1976_UCS_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer',
show_diagram_colours=True,
**kwargs):
"""
Plots the *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
show_diagram_colours : bool, optional
Whether to display the chromaticity diagram background colours.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> CIE_1976_UCS_chromaticity_diagram_plot() # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
if show_diagram_colours:
image = matplotlib.image.imread(
os.path.join(
PLOTTING_RESOURCES_DIRECTORY,
'CIE_1976_UCS_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 680)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
uv = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
wavelengths_chromaticity_coordinates = dict(zip(wavelengths, uv))
pylab.plot(uv[..., 0], uv[..., 1], color='black', linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]), (uv[-1][1], uv[0][1]),
color='black',
linewidth=2)
for label in labels:
u, v = wavelengths_chromaticity_coordinates[label]
pylab.plot(u, v, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates[right][0] -
wavelengths_chromaticity_coordinates[left][0])
dy = (wavelengths_chromaticity_coordinates[right][1] -
wavelengths_chromaticity_coordinates[left][1])
uv = np.array([u, v])
direction = np.array([-dy, dx])
normal = (np.array([
-dy, dx
]) if np.dot(normalise_vector(uv - equal_energy),
normalise_vector(direction)) > 0 else np.array([dy, -dx]))
normal = normalise_vector(normal)
normal /= 25
pylab.plot((u, u + normal[0] * 0.75), (v, v + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(u + normal[0],
v + normal[1],
label,
color='black',
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title':
'CIE 1976 UCS Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label':
'CIE u\'',
'y_label':
'CIE v\'',
'grid':
True,
'bounding_box': (0, 1, 0, 1)
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def plot_spectral_locus(cmfs='CIE 1931 2 Degree Standard Observer',
spectral_locus_colours=None,
spectral_locus_labels=None,
method='CIE 1931',
**kwargs):
"""
Plots the *Spectral Locus* according to given method.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions defining the
*Spectral Locus*.
spectral_locus_colours : array_like or unicode, optional
*Spectral Locus* colours, if ``spectral_locus_colours`` is set to
*RGB*, the colours will be computed according to the corresponding
chromaticity coordinates.
spectral_locus_labels : array_like, optional
Array of wavelength labels used to customise which labels will be drawn
around the spectral locus. Passing an empty array will result in no
wavelength labels being drawn.
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
*Chromaticity Diagram* method.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`, :func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_spectral_locus(spectral_locus_colours='RGB') # doctest: +SKIP
.. image:: ../_static/Plotting_Plot_Spectral_Locus.png
:align: center
:alt: plot_spectral_locus
"""
if spectral_locus_colours is None:
spectral_locus_colours = COLOUR_STYLE_CONSTANTS.colour.dark
settings = {'uniform': True}
settings.update(kwargs)
figure, axes = artist(**settings)
method = method.upper()
cmfs = first_item(filter_cmfs(cmfs).values())
illuminant = COLOUR_STYLE_CONSTANTS.colour.colourspace.whitepoint
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
if method == 'CIE 1931':
ij = XYZ_to_xy(cmfs.values, illuminant)
labels = ((390, 460, 470, 480, 490, 500, 510, 520, 540, 560, 580, 600,
620, 700)
if spectral_locus_labels is None else spectral_locus_labels)
elif method == 'CIE 1960 UCS':
ij = UCS_to_uv(XYZ_to_UCS(cmfs.values))
labels = ((420, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 610, 620, 630, 645, 680)
if spectral_locus_labels is None else spectral_locus_labels)
elif method == 'CIE 1976 UCS':
ij = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
labels = ((420, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 610, 620, 630, 645, 680)
if spectral_locus_labels is None else spectral_locus_labels)
else:
raise ValueError(
'Invalid method: "{0}", must be one of '
'{\'CIE 1931\', \'CIE 1960 UCS\', \'CIE 1976 UCS\'}'.format(
method))
pl_ij = tstack([
np.linspace(ij[0][0], ij[-1][0], 20),
np.linspace(ij[0][1], ij[-1][1], 20)
]).reshape(-1, 1, 2)
sl_ij = np.copy(ij).reshape(-1, 1, 2)
if spectral_locus_colours.upper() == 'RGB':
spectral_locus_colours = normalise_maximum(
XYZ_to_plotting_colourspace(cmfs.values), axis=-1)
if method == 'CIE 1931':
XYZ = xy_to_XYZ(pl_ij)
elif method == 'CIE 1960 UCS':
XYZ = xy_to_XYZ(UCS_uv_to_xy(pl_ij))
elif method == 'CIE 1976 UCS':
XYZ = xy_to_XYZ(Luv_uv_to_xy(pl_ij))
purple_line_colours = normalise_maximum(
XYZ_to_plotting_colourspace(XYZ.reshape(-1, 3)), axis=-1)
else:
purple_line_colours = spectral_locus_colours
for slp_ij, slp_colours in ((pl_ij, purple_line_colours),
(sl_ij, spectral_locus_colours)):
line_collection = LineCollection(
np.concatenate([slp_ij[:-1], slp_ij[1:]], axis=1),
colors=slp_colours)
axes.add_collection(line_collection)
wl_ij = dict(tuple(zip(wavelengths, ij)))
for label in labels:
i, j = wl_ij[label]
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else wavelengths[-1])
dx = wl_ij[right][0] - wl_ij[left][0]
dy = wl_ij[right][1] - wl_ij[left][1]
ij = np.array([i, j])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx]) if np.dot(
normalise_vector(ij - equal_energy), normalise_vector(direction)) >
0 else np.array([dy, -dx]))
normal = normalise_vector(normal) / 30
label_colour = (spectral_locus_colours
if is_string(spectral_locus_colours) else
spectral_locus_colours[index])
axes.plot(
(i, i + normal[0] * 0.75), (j, j + normal[1] * 0.75),
color=label_colour)
axes.plot(i, j, 'o', color=label_colour)
axes.text(
i + normal[0],
j + normal[1],
label,
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
settings = {'axes': axes}
settings.update(kwargs)
return render(**kwargs)
def CIE_1976_UCS_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer',
show_diagram_colours=True,
**kwargs):
"""
Plots the *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
show_diagram_colours : bool, optional
Display the chromaticity diagram background colours.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> CIE_1976_UCS_chromaticity_diagram_plot() # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
if show_diagram_colours:
image = matplotlib.image.imread(
os.path.join(PLOTTING_RESOURCES_DIRECTORY,
'CIE_1976_UCS_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530,
540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 680)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
uv = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
wavelengths_chromaticity_coordinates = dict(zip(wavelengths, uv))
pylab.plot(uv[..., 0], uv[..., 1], color='black', linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color='black',
linewidth=2)
for label in labels:
u, v = wavelengths_chromaticity_coordinates.get(label)
pylab.plot(u, v, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else
wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates.get(right)[0] -
wavelengths_chromaticity_coordinates.get(left)[0])
dy = (wavelengths_chromaticity_coordinates.get(right)[1] -
wavelengths_chromaticity_coordinates.get(left)[1])
uv = np.array([u, v])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx])
if np.dot(normalise_vector(uv - equal_energy),
normalise_vector(direction)) > 0 else
np.array([dy, -dx]))
normal = normalise_vector(normal)
normal /= 25
pylab.plot((u, u + normal[0] * 0.75),
(v, v + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(u + normal[0],
v + normal[1],
label,
color='black',
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title': 'CIE 1976 UCS Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label': 'CIE u\'',
'y_label': 'CIE v\'',
'grid': True,
'bounding_box': (0, 1, 0, 1)})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def CIE_1931_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer',
show_diagram_colours=True,
**kwargs):
"""
Plots the *CIE 1931 Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
show_diagram_colours : bool, optional
Display the chromaticity diagram background colours.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> CIE_1931_chromaticity_diagram_plot() # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
if show_diagram_colours:
image = matplotlib.image.imread(
os.path.join(PLOTTING_RESOURCES_DIRECTORY,
'CIE_1931_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (
390, 460, 470, 480, 490, 500, 510, 520, 540, 560, 580, 600, 620, 700)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
xy = XYZ_to_xy(cmfs.values, illuminant)
wavelengths_chromaticity_coordinates = dict(tuple(zip(wavelengths, xy)))
pylab.plot(xy[..., 0], xy[..., 1], color='black', linewidth=2)
pylab.plot((xy[-1][0], xy[0][0]),
(xy[-1][1], xy[0][1]),
color='black',
linewidth=2)
for label in labels:
x, y = wavelengths_chromaticity_coordinates.get(label)
pylab.plot(x, y, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else
wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates.get(right)[0] -
wavelengths_chromaticity_coordinates.get(left)[0])
dy = (wavelengths_chromaticity_coordinates.get(right)[1] -
wavelengths_chromaticity_coordinates.get(left)[1])
xy = np.array([x, y])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx])
if np.dot(normalise_vector(xy - equal_energy),
normalise_vector(direction)) > 0 else
np.array([dy, -dx]))
normal = normalise_vector(normal)
normal /= 25
pylab.plot((x, x + normal[0] * 0.75),
(y, y + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(x + normal[0],
y + normal[1],
label,
color='black',
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title': 'CIE 1931 Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label': 'CIE x',
'y_label': 'CIE y',
'grid': True,
'bounding_box': (0, 1, 0, 1)})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def plot_spectral_locus(cmfs='CIE 1931 2 Degree Standard Observer',
spectral_locus_colours=None,
spectral_locus_labels=None,
method='CIE 1931',
**kwargs):
"""
Plots the *Spectral Locus* according to given method.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions defining the
*Spectral Locus*.
spectral_locus_colours : array_like or unicode, optional
*Spectral Locus* colours, if ``spectral_locus_colours`` is set to
*RGB*, the colours will be computed according to the corresponding
chromaticity coordinates.
spectral_locus_labels : array_like, optional
Array of wavelength labels used to customise which labels will be drawn
around the spectral locus. Passing an empty array will result in no
wavelength labels being drawn.
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
*Chromaticity Diagram* method.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`, :func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_spectral_locus(spectral_locus_colours='RGB') # doctest: +SKIP
.. image:: ../_static/Plotting_Plot_Spectral_Locus.png
:align: center
:alt: plot_spectral_locus
"""
if spectral_locus_colours is None:
spectral_locus_colours = COLOUR_STYLE_CONSTANTS.colour.dark
settings = {'uniform': True}
settings.update(kwargs)
_figure, axes = artist(**settings)
method = method.upper()
cmfs = first_item(filter_cmfs(cmfs).values())
illuminant = COLOUR_STYLE_CONSTANTS.colour.colourspace.whitepoint
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
if method == 'CIE 1931':
ij = XYZ_to_xy(cmfs.values, illuminant)
labels = ((390, 460, 470, 480, 490, 500, 510, 520, 540, 560, 580, 600,
620, 700)
if spectral_locus_labels is None else spectral_locus_labels)
elif method == 'CIE 1960 UCS':
ij = UCS_to_uv(XYZ_to_UCS(cmfs.values))
labels = ((420, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 610, 620, 630, 645, 680)
if spectral_locus_labels is None else spectral_locus_labels)
elif method == 'CIE 1976 UCS':
ij = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
labels = ((420, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 610, 620, 630, 645, 680)
if spectral_locus_labels is None else spectral_locus_labels)
else:
raise ValueError(
'Invalid method: "{0}", must be one of '
'{{\'CIE 1931\', \'CIE 1960 UCS\', \'CIE 1976 UCS\'}}'.format(
method))
pl_ij = tstack([
np.linspace(ij[0][0], ij[-1][0], 20),
np.linspace(ij[0][1], ij[-1][1], 20)
]).reshape(-1, 1, 2)
sl_ij = np.copy(ij).reshape(-1, 1, 2)
if spectral_locus_colours.upper() == 'RGB':
spectral_locus_colours = normalise_maximum(
XYZ_to_plotting_colourspace(cmfs.values), axis=-1)
if method == 'CIE 1931':
XYZ = xy_to_XYZ(pl_ij)
elif method == 'CIE 1960 UCS':
XYZ = xy_to_XYZ(UCS_uv_to_xy(pl_ij))
elif method == 'CIE 1976 UCS':
XYZ = xy_to_XYZ(Luv_uv_to_xy(pl_ij))
purple_line_colours = normalise_maximum(
XYZ_to_plotting_colourspace(XYZ.reshape(-1, 3)), axis=-1)
else:
purple_line_colours = spectral_locus_colours
for slp_ij, slp_colours in ((pl_ij, purple_line_colours),
(sl_ij, spectral_locus_colours)):
line_collection = LineCollection(
np.concatenate([slp_ij[:-1], slp_ij[1:]], axis=1),
colors=slp_colours)
axes.add_collection(line_collection)
wl_ij = dict(tuple(zip(wavelengths, ij)))
for label in labels:
i, j = wl_ij[label]
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else wavelengths[-1])
dx = wl_ij[right][0] - wl_ij[left][0]
dy = wl_ij[right][1] - wl_ij[left][1]
ij = np.array([i, j])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx]) if np.dot(
normalise_vector(ij - equal_energy), normalise_vector(direction)) >
0 else np.array([dy, -dx]))
normal = normalise_vector(normal) / 30
label_colour = (spectral_locus_colours
if is_string(spectral_locus_colours) else
spectral_locus_colours[index])
axes.plot(
(i, i + normal[0] * 0.75), (j, j + normal[1] * 0.75),
color=label_colour)
axes.plot(i, j, 'o', color=label_colour)
axes.text(
i + normal[0],
j + normal[1],
label,
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
settings = {'axes': axes}
settings.update(kwargs)
return render(**kwargs)
def plot_spectral_locus(
cmfs: Union[MultiSpectralDistributions, str, Sequence[Union[
MultiSpectralDistributions,
str]], ] = "CIE 1931 2 Degree Standard Observer",
spectral_locus_colours: Optional[Union[ArrayLike, str]] = None,
spectral_locus_opacity: Floating = 1,
spectral_locus_labels: Optional[Sequence] = None,
method: Union[Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"],
str] = "CIE 1931",
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot the *Spectral Locus* according to given method.
Parameters
----------
cmfs
Standard observer colour matching functions used for computing the
spectral locus boundaries. ``cmfs`` can be of any type or form
supported by the :func:`colour.plotting.filter_cmfs` definition.
spectral_locus_colours
Colours of the *Spectral Locus*, if ``spectral_locus_colours`` is set
to *RGB*, the colours will be computed according to the corresponding
chromaticity coordinates.
spectral_locus_opacity
Opacity of the *Spectral Locus*.
spectral_locus_labels
Array of wavelength labels used to customise which labels will be drawn
around the spectral locus. Passing an empty array will result in no
wavelength labels being drawn.
method
*Chromaticity Diagram* method.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`, :func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_spectral_locus(spectral_locus_colours='RGB') # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_Spectral_Locus.png
:align: center
:alt: plot_spectral_locus
"""
method = validate_method(method,
["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"])
spectral_locus_colours = optional(spectral_locus_colours,
CONSTANTS_COLOUR_STYLE.colour.dark)
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
cmfs = cast(MultiSpectralDistributions,
first_item(filter_cmfs(cmfs).values()))
illuminant = CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint
wavelengths = list(cmfs.wavelengths)
equal_energy = np.array([1 / 3] * 2)
if method == "cie 1931":
ij = XYZ_to_xy(cmfs.values, illuminant)
labels = cast(
Tuple,
optional(
spectral_locus_labels,
(
390,
460,
470,
480,
490,
500,
510,
520,
540,
560,
580,
600,
620,
700,
),
),
)
elif method == "cie 1960 ucs":
ij = UCS_to_uv(XYZ_to_UCS(cmfs.values))
labels = cast(
Tuple,
optional(
spectral_locus_labels,
(
420,
440,
450,
460,
470,
480,
490,
500,
510,
520,
530,
540,
550,
560,
570,
580,
590,
600,
610,
620,
630,
645,
680,
),
),
)
elif method == "cie 1976 ucs":
ij = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
labels = cast(
Tuple,
optional(
spectral_locus_labels,
(
420,
440,
450,
460,
470,
480,
490,
500,
510,
520,
530,
540,
550,
560,
570,
580,
590,
600,
610,
620,
630,
645,
680,
),
),
)
pl_ij = np.reshape(
tstack([
np.linspace(ij[0][0], ij[-1][0], 20),
np.linspace(ij[0][1], ij[-1][1], 20),
]),
(-1, 1, 2),
)
sl_ij = np.copy(ij).reshape(-1, 1, 2)
purple_line_colours: Optional[Union[ArrayLike, str]]
if str(spectral_locus_colours).upper() == "RGB":
spectral_locus_colours = normalise_maximum(XYZ_to_plotting_colourspace(
cmfs.values),
axis=-1)
if method == "cie 1931":
XYZ = xy_to_XYZ(pl_ij)
elif method == "cie 1960 ucs":
XYZ = xy_to_XYZ(UCS_uv_to_xy(pl_ij))
elif method == "cie 1976 ucs":
XYZ = xy_to_XYZ(Luv_uv_to_xy(pl_ij))
purple_line_colours = normalise_maximum(XYZ_to_plotting_colourspace(
np.reshape(XYZ, (-1, 3))),
axis=-1)
else:
purple_line_colours = spectral_locus_colours
for slp_ij, slp_colours in (
(pl_ij, purple_line_colours),
(sl_ij, spectral_locus_colours),
):
line_collection = LineCollection(
np.concatenate([slp_ij[:-1], slp_ij[1:]], axis=1),
colors=slp_colours,
alpha=spectral_locus_opacity,
zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_scatter,
)
axes.add_collection(line_collection)
wl_ij = dict(zip(wavelengths, ij))
for label in labels:
ij_l = wl_ij.get(label)
if ij_l is None:
continue
ij_l = as_float_array([ij_l])
i, j = tsplit(ij_l)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else wavelengths[-1])
dx = wl_ij[right][0] - wl_ij[left][0]
dy = wl_ij[right][1] - wl_ij[left][1]
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx]) if np.dot(
normalise_vector(ij_l - equal_energy),
normalise_vector(direction),
) > 0 else np.array([dy, -dx]))
normal = normalise_vector(normal) / 30
label_colour = (
spectral_locus_colours if is_string(spectral_locus_colours) else
spectral_locus_colours[index] # type: ignore[index]
)
axes.plot(
(i, i + normal[0] * 0.75),
(j, j + normal[1] * 0.75),
color=label_colour,
alpha=spectral_locus_opacity,
zorder=CONSTANTS_COLOUR_STYLE.zorder.background_line,
)
axes.plot(
i,
j,
"o",
color=label_colour,
alpha=spectral_locus_opacity,
zorder=CONSTANTS_COLOUR_STYLE.zorder.background_line,
)
axes.text(
i + normal[0],
j + normal[1],
label,
clip_on=True,
ha="left" if normal[0] >= 0 else "right",
va="center",
fontdict={"size": "small"},
zorder=CONSTANTS_COLOUR_STYLE.zorder.background_label,
)
settings = {"axes": axes}
settings.update(kwargs)
return render(**kwargs)